|
| 1 | +import matplotlib.pyplot as plt |
| 2 | +import numpy as np |
| 3 | +from numba import njit |
| 4 | + |
| 5 | + |
| 6 | +@njit |
| 7 | +def hopalong_attractor(a, b, c, iterations=None): |
| 8 | + x_vals = np.zeros(iterations) |
| 9 | + y_vals = np.zeros(iterations) |
| 10 | + |
| 11 | + x, y = 0.0, 0.0 # Initial values |
| 12 | + |
| 13 | + for i in range(iterations): |
| 14 | + x, y = y - np.sign(x) * np.sqrt(abs(b * x - c)) , a - x |
| 15 | + |
| 16 | + x_vals[i] = x |
| 17 | + y_vals[i] = y |
| 18 | + |
| 19 | + return x_vals, y_vals |
| 20 | + |
| 21 | + |
| 22 | +def plot_hopalong_combined(x_vals, y_vals): |
| 23 | + iterations = range(len(x_vals)) |
| 24 | + amplitude = np.sqrt(np.diff(x_vals, prepend=x_vals[0])**2 + np.diff(y_vals, prepend=y_vals[0])**2) |
| 25 | + |
| 26 | + plt.figure(figsize=(12, 10)) |
| 27 | + |
| 28 | + plt.subplot(2, 2, 1, aspect='equal') |
| 29 | + plt.scatter(x_vals, y_vals, s=0.5, c='blue', alpha=0.7) |
| 30 | + plt.title("Hopalong Attractor") |
| 31 | + plt.xlabel("X") |
| 32 | + plt.ylabel("Y") |
| 33 | + plt.grid(True) |
| 34 | + |
| 35 | + plt.subplot(2, 1, 2) |
| 36 | + plt.plot(iterations, amplitude, label="Amplitude (Point Distance)", color="blue", alpha=0.7) |
| 37 | + plt.title("Amplitude of Hopalong Attractor Over Events") |
| 38 | + plt.xlabel("Iteration Index") |
| 39 | + plt.ylabel("Amplitude (Distance)") |
| 40 | + plt.xscale('log') |
| 41 | + plt.grid(True) |
| 42 | + plt.legend() |
| 43 | + |
| 44 | + plt.tight_layout() |
| 45 | + plt.show() |
| 46 | + |
| 47 | +def main(): |
| 48 | + |
| 49 | + a, b, c = 0.7, 0.4, 0 |
| 50 | + iterations = 10000000 |
| 51 | + |
| 52 | + x_vals, y_vals = hopalong_attractor(a, b, c, iterations) |
| 53 | + |
| 54 | + plot_hopalong_combined(x_vals, y_vals) |
| 55 | + |
| 56 | + |
| 57 | +if __name__ == "__main__": |
| 58 | + main() |
| 59 | + |
| 60 | + |
| 61 | + |
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